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Data Science with Tableau

  • Beginner
  • 18 and older
  • $1,510.50
  • 500 8th Ave, New York, NY
  • 20 hours over 8 sessions

Start Dates (0)

  • $1,510.50
  • NYC Data Science Academy @ 8th Ave @ 500 8th Ave Ste 905, New York, NY 10018
  • 20 hours over 8 sessions
  • Early bird price.
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Class Description

Description

What you'll learn in this data science course:

How can data visualizations be standardized and pipelined for viewing by key decision makers & analysts across an organization? Made to be compelling, informative, and appealing to the eye? Draw upon data sources as various as relational database servers (e.g. SQL), spreadsheets (e.g. Google Sheets), Salesforce, or web-based data? Process ‘big data’ in a live manner for the most up-to-date output? Through our accelerated introduction, students will become fluid in using Tableau’s features to achieve all of these objectives.

This course offers an accelerated intensive learning experience with Tableau – the growing standard in business intelligence for data visualization and dashboard creation. Without prior experience, students will learn to work with multiple data sources, create compelling visualizations, and roll out their data science products for continuous, scalable outputs to key stakeholders. 

By building insight and weaving narrative, students will be empowered to harness data in a striking way that provides value to organizations large and small. We utilized 4 user cases drawn from finance (public data from major stock exchanges) and sitcom data (Game of Throne 1 ).

Goals:
Without prior experience in data visualization or science, students can become fluid in this robust tool for business analysis & intelligence at any organization (from data-driven startup to Fortune 500 company). Students will learn first principles of visualization & dashboard creation, leverage Tableau’s features for combining and manipulating large & various sources of data, gain a deeper sense of comfort & practice by ‘learning through doing’ in frequent visualization labs, and complete a capstone visualization project that sparks their imagination.

The course is well-suited for:
  • Analysts/managers who frequently review data & share findings within an organization
  • Consultants & external advisors who frame performance indicators & metrics for key decision makers
  • Entrepreneurs growing companies where data is a central asset or offering
  • Data scientists interested in utilizing Tableau’s platform & R integration to pipeline compelling visualizations that harness advanced statistical learning algorithms
Prerequisites:
Know how to use Mac, Windows. Familiarity with relational databases will be nice but not required:
  • gain a greater appreciation for the logic underlying Tableau’s features
  • utilize their capstone project to visualize ‘big data’ by accessing a variety of server- or cloud-based sources
Before the course begins, pre-work will be available for students interested in strengthening their ability to access and extract data from relational databases (e.g. SQL-based servers)

Outcomes
By the end of the course, you will be able to:
  • Understand which visualizations best express a particular insight
  • Construct advanced visualizations such as tree maps, sunburst diagrams, and geo-mapped data
  • Wisely offer insight through visual dashboards constructed using principles such as the golden ratio
  • Pipeline visualizations that model large-scale data in a continuous fashion servers)
Syllabus:

Week 1
  • Importance of Tableau and How It Fits With Computing, Learning, & Analysis Today
  • Connecting with Data & Using Multiple Sources (Relational Logic, Joining, Blending)
  • Organizing your Data (Sorting, Filtering, Hierarchies, Groups, Subsets, Labeling, Aggregation)
  • Measures in View (Individual/Blended/Dual Axes, Cross-tabs, Highlight Tables, Reference Lines)
Week 2
  • Calculations in Tableau (Calculation Syntax & Functions, Level of Detail)
  • Creating and Using Parameters To Power Interactive Visualizations
  • Visualizing Relationships Between Numerical Values (Scatter Plots, Heat Maps)
  • Visualizing Breakdowns of the Whole (Boxplots, Tree Maps, Donut Chart, Sunburst Diagrams)
Week 3
  • Visualizing Structure, Relationships, & Trends through Machine Learning (Clustering, Regression, Forecasting, Integrating R Libraries)
  • Mapping Data Geographically
  • Bringing Together Visualization To Offer Insight & Narrative (Dashboards, Stories)
Week 4
  • Develop capstone project using your own data and have your own goal
  • Project deliverable sheet
School Notes: We offer a certification licensed by the NYS Board of Education.

Refund Policy

Any student wishing to withdraw from a program must notify CourseHorse in writing. The date of withdrawal for refund purposes is the last date of physical attendance. The failure of a student to notify us in writing of withdrawal may delay refund of tuition due pursuant to Section 5001 and 5002 of the Education Law.

Any student requesting cancellation within seven days after signing the Enrollment Agreement but before instruction begins will be refunded all money paid less 5% cancellation fee. Thereafter, in the event of cancellation or termination by the school, refunds will be prorated based on the student's last date of attendance.

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Questions & Answers (1)

Get quick answers from CourseHorse and past students.

Question from Katherine M.
Hi there, Is a computer supplied in the class or do students have to bring their personal laptops?
Answer from Brenda L. CourseHorse StaffCourseHorse Staff
Hi Katy! Computers are not provided. The student needs to bring a laptop with the software installed. Hope this helps.
Answer from Katherine M.
Yes. Thanks.
Answer Show all 2 answers
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NYC Data Science Academy

NYC Data Science Academy is a program designed to teach those who wish to learn.

Through hands-on projects and real-world applications, our students develop the skills they will need to pursue data science as both a hobby and profession. We also organize the NYC Open Data Meetup, which means that by...

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NYC Data Science Academy

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